Depth information in image data can also be learned implicitly, by directly transforming features from images to 3D space and finally to bird's-eye-view (BEV) grids [1]}, [2]}. Implicit methods, however, tend to suffer from feature smearing, wherein similar image features can exist at multiple locations in the projected space. Feature smearing increases the difficulty of localizing objects in the scene.
